{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 脉冲神经元模型\n",
    "\n",
    "作者: [赵振宇](https://github.com/15947470421)\n",
    "\n",
    "感谢朱文凯为本教程提供的建议"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "脉冲神经元模型是脉冲神经网络的基础，本章节我们将学习脉冲神经元模型。\n",
    "\n",
    "人工神经元模型是一个乘累加过程，最终的输出为一个具体的数值。而脉冲神经元的行为与生物神经元高度类似：神经元接受前置神经元的信号，改变膜电压。当膜电压大于阈值后，产生一个输出脉冲，膜电位复位。最终的输出为脉冲的有无。\n",
    "\n",
    "人工神经元和脉冲神经元模型的区别，类似于电路中，从模拟量到数字量的转变。\n",
    "\n",
    "`spikingjelly.activation_based.neuron`中定义了各种常见的脉冲神经元模型，我们以`spikingjelly.activation_based.neuron.IFNode`为例来介绍脉冲神经元。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import\n",
    "import torch\n",
    "from spikingjelly.activation_based import neuron # spikingjelly框架中定义神经元的库\n",
    "from spikingjelly import visualizing\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# 定义1个if神经元层\n",
    "if_layer = neuron.IFNode()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "初始化的IF神经元电压为0，我们可以通过.v来查看神经元膜电压"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "if_layer.v=0.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"if_layer.v={if_layer.v}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 神经元数量\n",
    "你可能会好奇这一层脉冲神经元的数量是多少。我们给与几个不同的输入，观察该层神经元的shape，可以发现该层神经元的数量与输入的shape是一致的。也就是说，该层神经元的个数与上一层的输入相同。下面我们通过几个实际的例子来进行说明：\n",
    "\n",
    "1. 上一层有5个信号输入，if_layer生成5个神经元\n",
    "2. 上一层有7个信号输入，if_layer生成7个神经元\n",
    "3. 上一层有3组神经元，每组均有5个信号输入，最终是一个[3, 5]的数组类型，if_layer生成[3, 5]个神经元"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x.shape=torch.Size([5]), if_layer.v.shape=torch.Size([5])\n",
      "x.shape=torch.Size([7]), if_layer.v.shape=torch.Size([7])\n",
      "x.shape=torch.Size([3, 5]), if_layer.v.shape=torch.Size([3, 5])\n"
     ]
    }
   ],
   "source": [
    "# 上一层有5个信号输入，if_layer生成5个神经元\n",
    "x = torch.rand(size=[5])\n",
    "if_layer(x)\n",
    "print(f'x.shape={x.shape}, if_layer.v.shape={if_layer.v.shape}')\n",
    "# x.shape=torch.Size([5]), if_layer.v.shape=torch.Size([5])\n",
    "if_layer.reset() # 注意，使用完神经元后需要复位\n",
    "\n",
    "# 上一层有7个信号输入，if_layer生成7个神经元\n",
    "x = torch.rand(size=[7])\n",
    "if_layer(x)\n",
    "print(f'x.shape={x.shape}, if_layer.v.shape={if_layer.v.shape}')\n",
    "# x.shape=torch.Size([7]), if_layer.v.shape=torch.Size([7])\n",
    "if_layer.reset() # 注意，使用完神经元后需要复位\n",
    "\n",
    "# 上一层有3组神经元，每组均有5个信号输入[3, 5]，if_layer生成[3, 5]个神经元\n",
    "x = torch.rand(size=[3, 5])\n",
    "if_layer(x)\n",
    "print(f'x.shape={x.shape}, if_layer.v.shape={if_layer.v.shape}')\n",
    "# x.shape=torch.Size([3, 5]), if_layer.v.shape=torch.Size([3, 5])\n",
    "if_layer.reset() # 注意，使用完神经元后需要复位"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来，让我们来观察一下脉冲神经元的膜电压随时间的变化：\n",
    "\n",
    "我们设定总时间`T=150`，每一个时刻均给予脉冲神经元输入信号电压`x=0.02V`。\n",
    "\n",
    "通过SJ框架提供的`visualizing.plot_one_neuron_v_s`函数，我们可以直接画出神经元的膜电压V和输出脉冲S随时间变化的图像。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "input: tensor([0.0200])\n",
      "votage: [tensor([0.0200]), tensor([0.0400]), tensor([0.0600]), tensor([0.0800]), tensor([0.1000]), tensor([0.1200]), tensor([0.1400]), tensor([0.1600]), tensor([0.1800]), tensor([0.2000]), tensor([0.2200]), tensor([0.2400]), tensor([0.2600]), tensor([0.2800]), tensor([0.3000]), tensor([0.3200]), tensor([0.3400]), tensor([0.3600]), tensor([0.3800]), tensor([0.4000]), tensor([0.4200]), tensor([0.4400]), tensor([0.4600]), tensor([0.4800]), tensor([0.5000]), tensor([0.5200]), tensor([0.5400]), tensor([0.5600]), tensor([0.5800]), tensor([0.6000]), tensor([0.6200]), tensor([0.6400]), tensor([0.6600]), tensor([0.6800]), tensor([0.7000]), tensor([0.7200]), tensor([0.7400]), tensor([0.7600]), tensor([0.7800]), tensor([0.8000]), tensor([0.8200]), tensor([0.8400]), tensor([0.8600]), tensor([0.8800]), tensor([0.9000]), tensor([0.9200]), tensor([0.9400]), tensor([0.9600]), tensor([0.9800]), tensor([1.0000]), tensor([0.]), tensor([0.0200]), tensor([0.0400]), tensor([0.0600]), tensor([0.0800]), tensor([0.1000]), tensor([0.1200]), tensor([0.1400]), tensor([0.1600]), tensor([0.1800]), tensor([0.2000]), tensor([0.2200]), tensor([0.2400]), tensor([0.2600]), tensor([0.2800]), tensor([0.3000]), tensor([0.3200]), tensor([0.3400]), tensor([0.3600]), tensor([0.3800]), tensor([0.4000]), tensor([0.4200]), tensor([0.4400]), tensor([0.4600]), tensor([0.4800]), tensor([0.5000]), tensor([0.5200]), tensor([0.5400]), tensor([0.5600]), tensor([0.5800]), tensor([0.6000]), tensor([0.6200]), tensor([0.6400]), tensor([0.6600]), tensor([0.6800]), tensor([0.7000]), tensor([0.7200]), tensor([0.7400]), tensor([0.7600]), tensor([0.7800]), tensor([0.8000]), tensor([0.8200]), tensor([0.8400]), tensor([0.8600]), tensor([0.8800]), tensor([0.9000]), tensor([0.9200]), tensor([0.9400]), tensor([0.9600]), tensor([0.9800]), tensor([1.0000]), tensor([0.]), tensor([0.0200]), tensor([0.0400]), tensor([0.0600]), tensor([0.0800]), tensor([0.1000]), tensor([0.1200]), tensor([0.1400]), tensor([0.1600]), tensor([0.1800]), tensor([0.2000]), tensor([0.2200]), tensor([0.2400]), tensor([0.2600]), tensor([0.2800]), tensor([0.3000]), tensor([0.3200]), tensor([0.3400]), tensor([0.3600]), tensor([0.3800]), tensor([0.4000]), tensor([0.4200]), tensor([0.4400]), tensor([0.4600]), tensor([0.4800]), tensor([0.5000]), tensor([0.5200]), tensor([0.5400]), tensor([0.5600]), tensor([0.5800]), tensor([0.6000]), tensor([0.6200]), tensor([0.6400]), tensor([0.6600]), tensor([0.6800]), tensor([0.7000]), tensor([0.7200]), tensor([0.7400]), tensor([0.7600]), tensor([0.7800]), tensor([0.8000]), tensor([0.8200]), tensor([0.8400]), tensor([0.8600]), tensor([0.8800]), tensor([0.9000]), tensor([0.9200]), tensor([0.9400]), tensor([0.9600])]\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = 150\n",
    "if_layer.reset() # 神经元复位\n",
    "x = torch.as_tensor([0.02])\n",
    "print(\"input:\", x)\n",
    "s_list = [] # 记录输出脉冲\n",
    "v_list = [] # 记录输出膜电压\n",
    "# 按照时间顺序逐步进行\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x))\n",
    "    v_list.append(if_layer.v)\n",
    "\n",
    "print(\"votage:\", v_list) # 输出膜电压\n",
    "dpi = 100 # 设置输出图片大小\n",
    "figsize = (12, 8) # 设置输出图片比例\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以看到，随着时间的增加，膜电压每一个时刻增加0.02V，也就是将输入的信号x，增加到膜电位上。\n",
    "\n",
    "默认的膜电压阈值为1V。因此，当膜电压小于1V时，没有产生脉冲。当膜电压累加到IF神经元默认的阈值电压1V时，神经元发出一个脉冲，并且膜电位复位到0V。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "上面的仿真，我们假设输入的信号一直为0.02V，接下来我们使用随机的输入信号电压值。我们设定总时间$T=50$，每一步的输入信号电压$x=[0.0 , 0.1]V$。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0060, 0.0573, 0.0674, 0.0530, 0.0227, 0.0479, 0.0282, 0.0509, 0.0134,\n",
      "        0.0249, 0.0652, 0.0022, 0.0321, 0.0811, 0.0888, 0.0005, 0.0007, 0.0672,\n",
      "        0.0655, 0.0784, 0.0820, 0.0517, 0.0449, 0.0692, 0.0025, 0.0225, 0.0298,\n",
      "        0.0174, 0.0163, 0.0471, 0.0925, 0.0083, 0.0326, 0.0311, 0.0292, 0.0889,\n",
      "        0.0500, 0.0300, 0.0071, 0.0011, 0.0969, 0.0081, 0.0979, 0.0288, 0.0167,\n",
      "        0.0384, 0.0688, 0.0452, 0.0385, 0.0038])\n",
      "v_list = [tensor([0.0060]), tensor([0.0633]), tensor([0.1306]), tensor([0.1836]), tensor([0.2063]), tensor([0.2542]), tensor([0.2824]), tensor([0.3334]), tensor([0.3468]), tensor([0.3717]), tensor([0.4369]), tensor([0.4391]), tensor([0.4713]), tensor([0.5524]), tensor([0.6412]), tensor([0.6418]), tensor([0.6424]), tensor([0.7096]), tensor([0.7751]), tensor([0.8534]), tensor([0.9355]), tensor([0.9872]), tensor([0.]), tensor([0.0692]), tensor([0.0716]), tensor([0.0941]), tensor([0.1239]), tensor([0.1413]), tensor([0.1576]), tensor([0.2047]), tensor([0.2972]), tensor([0.3055]), tensor([0.3381]), tensor([0.3691]), tensor([0.3983]), tensor([0.4872]), tensor([0.5372]), tensor([0.5672]), tensor([0.5744]), tensor([0.5754]), tensor([0.6723]), tensor([0.6804]), tensor([0.7783]), tensor([0.8070]), tensor([0.8237]), tensor([0.8621]), tensor([0.9309]), tensor([0.9761]), tensor([0.]), tensor([0.0038])]\n",
      "s_list = [tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([1.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([1.]), tensor([0.])]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = 50\n",
    "if_layer.reset()\n",
    "x = torch.rand(T) / 10. # 随机生成长度为T的输入，最后缩小10倍\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x[t]).unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "    v_list.append(if_layer.v.unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "\n",
    "print(f\"v_list = {v_list}\")\n",
    "print(f\"s_list = {s_list}\")\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过输出图像可以看到，由于输入的信号为随机值，因此每一时刻膜电压的增量不再相同，不再是平滑的三角波。\n",
    "\n",
    "如果我们希望更改阈值电压`v threshold`或者替代函数`surrogate function`，SJ框架也提供了非常方便的API。\n",
    "\n",
    "IFNode共有7个参数可以设置，具体的参数介绍可以查看class IFNode的简介。\n",
    "+ `v_threshold`: 神经元的阈值电压\n",
    "+ `v_reset`: 神经元的重置电压。如果不为 ``None``，当神经元释放脉冲后，电压会被重置为 ``v_reset``；\n",
    "    如果设置为 ``None``，当神经元释放脉冲后，电压会被减去 ``v_threshold``\n",
    "+ `surrogate_function`: 反向传播时用来计算脉冲函数梯度的替代函数\n",
    "+ `detach_reset`: 是否将reset过程的计算图分离\n",
    "+ `step_mode`: 步进模式，可以为 `'s'` (单步) 或 `'m'` (多步)\n",
    "+ `backend`: 使用那种后端。不同的 ``step_mode`` 可能会带有不同的后端。可以通过打印 ``self.supported_backends`` 查看当前\n",
    "    使用的步进模式支持的后端。在支持的情况下，使用 ``'cupy'`` 后端是速度最快的\n",
    "+ `store_v_seq`: 在使用 ``step_mode = 'm'`` 时，给与 ``shape = [T, N, *]`` 的输入后，是否保存中间过程的 ``shape = [T, N, *]``\n",
    "    的各个时间步的电压值 ``self.v_seq`` 。设置为 ``False`` 时计算完成后只保留最后一个时刻的电压，即 ``shape = [N, *]`` 的 ``self.v`` 。\n",
    "    通常设置成 ``False`` ，可以节省内存\n",
    "\n",
    "下面我们将神经元的阈值电压`v threshold`更改为2V，替代函数`surrogate function`更改为`ATan`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0339, 0.0251, 0.0641, 0.0263, 0.0982, 0.0668, 0.0399, 0.0985, 0.0933,\n",
      "        0.0578, 0.0323, 0.0479, 0.0262, 0.0354, 0.0854, 0.0702, 0.0138, 0.0609,\n",
      "        0.0554, 0.0522, 0.0776, 0.0887, 0.0274, 0.0187, 0.0090, 0.0263, 0.0602,\n",
      "        0.0684, 0.0247, 0.0264, 0.0292, 0.0262, 0.0707, 0.0550, 0.0840, 0.0368,\n",
      "        0.0512, 0.0954, 0.0598, 0.0980, 0.0280, 0.0858, 0.0085, 0.0449, 0.0264,\n",
      "        0.0916, 0.0934, 0.0376, 0.0750, 0.0264])\n",
      "v_list = [tensor([0.0339]), tensor([0.0590]), tensor([0.1231]), tensor([0.1495]), tensor([0.2477]), tensor([0.3144]), tensor([0.3543]), tensor([0.4529]), tensor([0.5462]), tensor([0.6039]), tensor([0.6363]), tensor([0.6842]), tensor([0.7103]), tensor([0.7458]), tensor([0.8312]), tensor([0.9014]), tensor([0.9152]), tensor([0.9761]), tensor([1.0316]), tensor([1.0838]), tensor([1.1614]), tensor([1.2501]), tensor([1.2774]), tensor([1.2962]), tensor([1.3052]), tensor([1.3315]), tensor([1.3916]), tensor([1.4600]), tensor([1.4847]), tensor([1.5112]), tensor([1.5404]), tensor([1.5666]), tensor([1.6373]), tensor([1.6923]), tensor([1.7763]), tensor([1.8131]), tensor([1.8644]), tensor([1.9597]), tensor([0.]), tensor([0.0980]), tensor([0.1260]), tensor([0.2118]), tensor([0.2203]), tensor([0.2651]), tensor([0.2915]), tensor([0.3831]), tensor([0.4765]), tensor([0.5141]), tensor([0.5891]), tensor([0.6154])]\n",
      "s_list = [tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([1.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.])]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from spikingjelly.activation_based import surrogate # 引入替代函数库\n",
    "T = 50\n",
    "if_layer.reset()\n",
    "if_layer.v_threshold=2.0\n",
    "if_layer.surrogate_function=surrogate.ATan()\n",
    "\n",
    "x = torch.rand(T) / 10. # 随机生成长度为T的输入，最后缩小10倍\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x[t]).unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "    v_list.append(if_layer.v.unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "\n",
    "print(f\"v_list = {v_list}\")\n",
    "print(f\"s_list = {s_list}\")\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "更改后，当膜电压增加到2.0V时，才会发出脉冲。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "目前为止，我们还只是仿真一个神经元，通常，一层神经元由很多个神经元组成。\n",
    "\n",
    "下面让我们拓展到仿真多个神经元，其中，每一个神经元仍只有1个输入信号。\n",
    "\n",
    "SJ框架提供`visualizing.plot_2d_heatmap`函数，可以画出多个神经元的膜电压随时间的变化热力图像，颜色越浅，表明膜电压越高。\n",
    "\n",
    "SJ框架提供`visualizing.plot_1d_spikes`函数，可以画出多个神经元随时间变化输出的脉冲，并统计发射脉冲的频率`firing rate`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x = tensor([0.0221, 0.0497, 0.0194, 0.0543, 0.0010, 0.0346, 0.0897, 0.0124, 0.0940,\n",
      "        0.0510])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = 50\n",
    "N = 10 # 神经元个数N(num_neuron)\n",
    "if_layer.reset()\n",
    "x = torch.rand(N) / 10. # 随机生成长度为N(num_neuron)的输入，最后缩小10倍\n",
    "print(f\"x = {x}\")\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x).unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "    v_list.append(if_layer.v.unsqueeze(0)) # .unsqueeze确保维度正确\n",
    "\n",
    "s_list = torch.cat(s_list) # 整合为1个tensor\n",
    "v_list = torch.cat(v_list) # 整合为1个tensor\n",
    "\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_2d_heatmap(array=v_list.numpy(), title='membrane potentials', xlabel='simulating step',\n",
    "                            ylabel='neuron index', int_x_ticks=True, x_max=T, figsize=figsize, dpi=dpi)\n",
    "\n",
    "\n",
    "visualizing.plot_1d_spikes(spikes=s_list.numpy(), title='membrane sotentials', xlabel='simulating step',\n",
    "                        ylabel='neuron index', figsize=figsize, dpi=dpi)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "注意，我们这里只是生成了一个输入信号向量，在每一个时间步长中，同一个神经元的输入信号均相同。也就是说每一个时间步长的循环中，输入均为向量x，同一个神经元的膜电位增量均相同，说明输入信号一直相同。\n",
    "\n",
    "如果我们想让每一个时刻的输入信号都不同，那么就要将x拓展一个时间维度，从一个向量拓展为一个矩阵。矩阵的每一行代表一个时刻的所有神经元输入信号，每一列代表每一个神经元的输入信号。最终输入信号`x.shape = [T, N]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x.shape = torch.Size([50, 10])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T = 50\n",
    "N = 10 # 神经元个数\n",
    "if_layer.reset()\n",
    "x = torch.rand([T, N]) / 3. # 随机生成大小为[T, N]的输入，最后缩小5倍\n",
    "print(f\"x.shape = {x.shape}\")\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x[t]).unsqueeze(0))\n",
    "    v_list.append(if_layer.v.unsqueeze(0))\n",
    "\n",
    "s_list = torch.cat(s_list)\n",
    "v_list = torch.cat(v_list)\n",
    "\n",
    "figsize = (12, 8)\n",
    "dpi = 100\n",
    "visualizing.plot_2d_heatmap(array=v_list.numpy(), title='membrane potentials', xlabel='simulating step',\n",
    "                            ylabel='neuron index', int_x_ticks=True, x_max=T, figsize=figsize, dpi=dpi)\n",
    "\n",
    "\n",
    "visualizing.plot_1d_spikes(spikes=s_list.numpy(), title='membrane sotentials', xlabel='simulating step',\n",
    "                        ylabel='neuron index', figsize=figsize, dpi=dpi)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "同一个神经元的输出脉冲时间间隔都不相同，说明输入信号随时间变化。\n",
    "\n",
    "上面的方法我们是通过循环的方法实现多步时间的，惊蛰框架提供了多步模式，可以更简洁和方便的实现多步时间。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if_layer.reset() # 复位神经元\n",
    "if_layer.step_mode = 'm' # 设置神经元为多步模式\n",
    "if_layer.store_v_seq = True # 保存每一个时刻的膜电压\n",
    "x = torch.rand([T, N]) / 5. # 生成输入数据\n",
    "spike = if_layer(x)\n",
    "\n",
    "figsize = (12, 8)\n",
    "dpi = 100\n",
    "visualizing.plot_2d_heatmap(array=v_list.numpy(), title='membrane potentials', xlabel='simulating step',\n",
    "                            ylabel='neuron index', int_x_ticks=True, x_max=T, figsize=figsize, dpi=dpi)\n",
    "\n",
    "\n",
    "visualizing.plot_1d_spikes(spikes=spike.numpy(), title='membrane sotentials', xlabel='simulating step',\n",
    "                        ylabel='neuron index', figsize=figsize, dpi=dpi)\n",
    "\n",
    "if_layer.reset()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LIF神经元模型：\n",
    "\n",
    "Leaky Integrate-and-Fire(LIF) 神经元模型，可以看作是带漏电效应的IF神经元模型（膜电压会随着时间缓慢下降）。当膜电压小于阈值时，LIF神经元的神经动力学方程为：\n",
    "\n",
    "若 ``decay_input == True``:\n",
    "    $H[t] = V[t-1] + \\frac{1}{\\tau}(X[t] - (V[t-1] - V_{reset}))$\n",
    "\n",
    "若 ``decay_input == False``:\n",
    "    $H[t] = V[t-1] - \\frac{1}{\\tau}(V[t-1] - V_{reset}) + X[t]$\n",
    "\n",
    "我们仿真IF神经元模型，以及时间常数分别为$tau=1，tau=2，tau=5$的LIF神经元模型\n",
    "\n",
    "输入的信号为仅在t=9时产生一个强度为0.99的脉冲，仿真周期`T=50`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.9900, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000])\n",
      "[tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900]), tensor([0.9900])]\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# IF神经元模型\n",
    "if_layer = neuron.IFNode()\n",
    "if_layer.reset() # 复位神经元\n",
    "T = 50\n",
    "x = torch.as_tensor([0.0]*10 + [0.99]*1 + [0.0]*39)\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x[t]).unsqueeze(0))\n",
    "    v_list.append(if_layer.v.unsqueeze(0))\n",
    "\n",
    "print(v_list)\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.9900, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000])\n",
      "[tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.9900]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.])]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LIF神经元模型tau=1\n",
    "lif_layer = neuron.LIFNode()\n",
    "lif_layer.tau = 1.\n",
    "lif_layer.reset()\n",
    "T = 50\n",
    "x = torch.as_tensor([0.0]*10 + [0.99]*1 + [0.0]*39)\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(lif_layer(x[t]).unsqueeze(0))\n",
    "    v_list.append(lif_layer.v.unsqueeze(0))\n",
    "\n",
    "print(v_list)\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.9900, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000])\n",
      "[tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.4950]), tensor([0.2475]), tensor([0.1238]), tensor([0.0619]), tensor([0.0309]), tensor([0.0155]), tensor([0.0077]), tensor([0.0039]), tensor([0.0019]), tensor([0.0010]), tensor([0.0005]), tensor([0.0002]), tensor([0.0001]), tensor([6.0425e-05]), tensor([3.0212e-05]), tensor([1.5106e-05]), tensor([7.5531e-06]), tensor([3.7766e-06]), tensor([1.8883e-06]), tensor([9.4414e-07]), tensor([4.7207e-07]), tensor([2.3603e-07]), tensor([1.1802e-07]), tensor([5.9009e-08]), tensor([2.9504e-08]), tensor([1.4752e-08]), tensor([7.3761e-09]), tensor([3.6880e-09]), tensor([1.8440e-09]), tensor([9.2201e-10]), tensor([4.6100e-10]), tensor([2.3050e-10]), tensor([1.1525e-10]), tensor([5.7626e-11]), tensor([2.8813e-11]), tensor([1.4406e-11]), tensor([7.2032e-12]), tensor([3.6016e-12]), tensor([1.8008e-12]), tensor([9.0040e-13])]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LIF神经元模型tau=2\n",
    "lif_layer = neuron.LIFNode()\n",
    "lif_layer.tau = 2.\n",
    "lif_layer.reset()\n",
    "T = 50\n",
    "x = torch.as_tensor([0.0]*10 + [0.99]*1 + [0.0]*39)\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(lif_layer(x[t]).unsqueeze(0))\n",
    "    v_list.append(lif_layer.v.unsqueeze(0))\n",
    "\n",
    "print(v_list)\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.9900, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000, 0.0000,\n",
      "        0.0000, 0.0000, 0.0000, 0.0000, 0.0000])\n",
      "[tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.]), tensor([0.1980]), tensor([0.1584]), tensor([0.1267]), tensor([0.1014]), tensor([0.0811]), tensor([0.0649]), tensor([0.0519]), tensor([0.0415]), tensor([0.0332]), tensor([0.0266]), tensor([0.0213]), tensor([0.0170]), tensor([0.0136]), tensor([0.0109]), tensor([0.0087]), tensor([0.0070]), tensor([0.0056]), tensor([0.0045]), tensor([0.0036]), tensor([0.0029]), tensor([0.0023]), tensor([0.0018]), tensor([0.0015]), tensor([0.0012]), tensor([0.0009]), tensor([0.0007]), tensor([0.0006]), tensor([0.0005]), tensor([0.0004]), tensor([0.0003]), tensor([0.0002]), tensor([0.0002]), tensor([0.0002]), tensor([0.0001]), tensor([0.0001]), tensor([8.0318e-05]), tensor([6.4255e-05]), tensor([5.1404e-05]), tensor([4.1123e-05]), tensor([3.2898e-05])]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LIF神经元模型tau=5\n",
    "lif_layer = neuron.LIFNode()\n",
    "lif_layer.tau = 5.\n",
    "lif_layer.reset()\n",
    "T = 50\n",
    "x = torch.as_tensor([0.0]*10 + [0.99]*1 + [0.0]*39)\n",
    "print(x)\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(lif_layer(x[t]).unsqueeze(0))\n",
    "    v_list.append(lif_layer.v.unsqueeze(0))\n",
    "\n",
    "print(v_list)\n",
    "dpi = 100\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过观察上面4个仿真结果，IF神经元模型没有衰减，没有输入的时候，膜电压保持不变。而LIF神经元模型的膜电压则会随时间衰减，最终趋向于0V。\n",
    "\n",
    "LIF神经元模型中参数`tau`的含义非常类似于电路中的RC时间常数，tau越大，表示该神经元对输入的响应以及膜电压衰减越缓慢，反之亦然。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "SpikingJelly_zzy",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
